Yinglian Xie On Raising $100 Million To Fight Fraud With AI-Powered Solutions

Yinglian Xie is the co-founder and CEO of DataVisor which is a fraud detection company powered by transformational AI technology. The company has raised $100 million from investors like NEA, Sequoia, GSR Ventures, and Genesis Capital.

In this episode you will learn:

Building networks at large corporations
Yinglian’s top advice for those considering launching their own startups
The differences between raising funding in the US and Asia
The many types of fraud DataVisor is helping its clients combat

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About Yinglian Xie:

Yinglian Xie is CEO and Co-Founder of DataVisor, a leading Silicon Valley-based technology company providing advanced fraud management solutions powered by artificial intelligence.

Before founding DataVisor, Yinglian Xie worked at Microsoft Research, where her focus was on advancing the security of online services with big data analytics and machine learning.

Yinglian Xie completed both her Ph.D. and post-doctoral work in Computer Science at Carnegie Mellon University, and currently holds over 20 patents in her field.

A highly-regarded researcher, author, and conference contributor, Yinglian Xie is widely regarded as one of the most influential figures in the areas of artificial intelligence, machine learning, and big data security.

Connect with Yinglian Xie:

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FULL TRANSCRIPTION OF THE INTERVIEW:

Alejandro: Alrighty. Hello everyone, and welcome to the DealMakers show. Today we have a very exciting female founder, and I think she’s going to teach us a lot about building and scaling and a lot about being a foreigner, just like myself coming here to the U.S. and really making it happen. Then, also, a lot about AI and then going from technical to business, and you name it. So, without further ado, let’s welcome our guest today. Yinglian Xie, welcome to the show.

Yinglian Xie: It’s my great pleasure to be here. Thank you for having me.

Alejandro: Originally, you were born and raised in China. Can you tell us about being raised there, and how was life in China?

Yinglian Xie: I was born and raised in Suzhou, actually a very beautiful city in China. Suzhou has a rich culture of being an old city, having a history of 2,500 years and above. Therefore, there’s a lot of focus on pursuing more academic studies, and there was that kind of rich culture. I feel it was quite uneventful and peaceful. My mother and father are the ones who always encouraged me to do well in school. I was always thinking during my early childhood that I wanted to grow up to be a scientist and to have a Ph.D. It was interesting because it seemed that was every child’s dream when we were growing up, so that’s what I thought about. I’ve been working toward that, and also being a good student following along until I went to college. I went to Peking University, one of the best universities in China. I went to Beijing, a different city, to experience a different culture. But I would say it was actually a very peaceful childhood to focus on academics like science. Probably, that shaped me to be who I am and to be where I was pursuing more of on the academic side.

Alejandro: Computer science: how did you get into computers?

Yinglian Xie: So far, computer science. It was a new concept. I wouldn’t say it was a choice by myself. Sort of knowing what it is to jump into that. I think I had some early exposure knowing when I grew up that I was not very pervasive to be accessible like computers to the kids those ages. It was a bit foreign to me. I had occasional access to computers when I was in middle school. They didn’t have a lot of the concept of computer science. When I was looking at Peking University, I was fascinated and wanted to go to that particular place. I entered that university. I was an early admission, waive of the entrance exam because I was one of the top students. My school principal picked the subject for me to some extent. I had a relative working at the China Academy of Science, who told me that was a good major. So, that was the start of it. It was not picked by me. It was very accidental, but I ended up loving it.

Alejandro: That’s amazing. Well, I’m very glad to hear that you have always been very much into academics. If I ever decide, Yinglian, to go back to school, I’ll definitely call you for the homework. [Laughter] Okay, I’ll keep you posted. Carnegie Mellon would be the next big milestone in your career, and obviously, what led you to come here to the U.S. So, tell us about this.

Yinglian Xie: I would say it was a continuation of pursuing the best study of the same thing that I had in my childhood. I was in the best high school in my hometown. My next step was that I wanted to go to the best college, which I did at Peking University in Beijing. I wanted to continue that. Since I was in computer science, and it was fascinating, and I loved the subject. Obviously, my next step was to fulfill my childhood dreams. I wanted to get a Ph.D. I wanted to go to the best place for that and the most advanced place. Carnegie Mellon University in the U.S. definitely was the best sort of place for me as a next step to pursue my graduate studies. So, it became a natural choice for me to say, “Let me apply to these top schools and these top advanced Ph.D. programs and see if I could get admitted. If I could, I would be thrilled to continue my childhood dream. That led me to the Carnegie Mellon University Computer Science Ph.D. program.

Alejandro: Very cool. Then after you did that, you started to get a lay of the land. You stayed there for quite a bit, but then Microsoft came into your life. How did this happen, and what was going on with Microsoft? Why did you decide to go and work for Microsoft?

Yinglian Xie: At that time, I stayed at Pittsburg for a long time. I wanted to continue to do research and be in that environment at Carnegie Mellon University. It was very proud of their early pioneers in computer science and the entire subject throughout the entire industry, and continuing to challenge that advance to take the mission to advance the state of art of the whole industry was everybody’s’ pursuit. The question after my graduation was, “Do I want to continue the academic path to some school and become a faculty, or should I pick an industry to do something entirely different.” Frankly, if you look at the industry, we could go down and jump into the industry of doing a hands-on job more in the engineering part. Or there could be the middle ground of research. To me, I’ve been so long in academia that I wanted to, at that time — it’s difficult to immediately say, “I want to be the other side in product engineering.” I wanted to continue doing research. But at the same time, I felt I had been in the ivory tower for long enough that I wanted an industry environment to see what other things, in reality, looked like that are different. So, that’s what I wanted to do. At the same time, I said, “If I want to go into industry research, what’s the best place to do it?” At that time, Microsoft’s research, I can tell you now, is probably one of the best research labs. My old choices of locations, Microsoft research, I have to say I’d take Silicon Valley, and I liked the Silicon Valley location because this is the place where you get the industry flavor and the research part. At the same time, you see a lot of new things going on in general, being in this area of the real world fighting things. For the particular lab, I think what attracted me were the colleagues that I got the chance to work with. We had a fantastic group of colleagues who previously worked at the PARC Lab. Xerox PARC was coming to Microsoft. These were the pioneers of the computer science industry, and they were the true award winners. These are the colleagues where I felt I could be inspired a lot to continue to pursue the best of and continue to advance the state of art but in a different environment. That’s what I felt, with no hesitation, was the place I wanted to go.

Alejandro: You stayed in Microsoft for something like seven years, quite a bit of time. This actually gave you one of the most important things, which was to meet your co-founder, Fang Yu, which is your co-founder at DataVisor. As a segue into DataVisor, we can start talking about battlefields and getting out there and making it happen, what were your three biggest takeaways from working for such a big organization like Microsoft. What would those three big takeaways be?

Yinglian Xie: I would say we worked at Microsoft at the same time. It was a specific environment of the research lab and was not also any Microsoft research lab. I would say Microsoft research, Silicon Valley. I highlight this because you have to understand the culture, the good, and the background was Xerox PARC Lab formally. What I felt out of this was also some of my best years. I enjoyed working there. I got the total freedom of being able to work on the topics that I was excited about and grateful for such an organization. I think it was kind of a luxury in having this research lab and having the freedom to let us have the opportunity to explore, to challenge the state of art, to do it. Second of all, although we got a lot of freedom, a lot of flexibility to do that for big organizations like Microsoft. If you want to make things, in reality, saying, “I want to turn my research result into something that impacts the industry, impacts the product teams, and in the end, impact everybody a little bit more directly. That’s very challenging to do because that’s a big organization that you need to collaborate with different teams and draw boundaries, and there’s resource investment. So, sometimes, things take time. And also, other times the cross-collaboration is going on that could potentially slow things down as well. That’s the second aspect of it. The third thing I learned from Microsoft is I got the opportunity to look at the problems that impact big enterprise for Microsoft the teams we work with. Many of them are consumer-facing. They actually work with hundreds and millions of users. The scale is phenomenal. I was lucky that I got the chance to access the hardest problems and bit data set, and at the same time, have access to a lot of computation power. That’s the leading of the industry at that time that empowered us to work on the type of research we wanted: big data, IA, machine learning, and moving onto this building user era that enabled us to study these topics inside and out. Then we came to the idea of DataVisor. When Fang and I decided we wanted to do DataVisor, we aimed high. We were able to come out of that environment to say our mission is we want to come up with a new framework that will tackle some of the hardest problems we’ve seen across these different teams. At the same time, we want to work with the largest enterprises in the world. We want to solve problems that impact all these consumers at extremely large scale. At the same time, the one thing we want to get out of DataVisor, which I mentioned Microsoft is a little more difficult to provide, we wanted to be able to come out of that research environment more tangibly and be able to have a company that turned these ideas into realities that could generate value for all companies and all customers and any large enterprise in the world. So that seemed a natural continuation, but in a completely different environment, we wanted to pursue that.

Alejandro: That’s quite an interesting change of path because here you are, coming from a family very much into academics, very much into the traditional route, probably they were super proud of seeing you now working at one of the tech giants. Here you are; you decide to give up on the traditional and the steady paycheck and 9 to 5, and you go at it, and you become an entrepreneur. So, tell us about that day or the events that happened leading up to that day when you and Fang said, “Let’s give our notice, and let’s start executing on this dream that we’ve incubated.”?

Yinglian Xie: That actually was quite interesting in the process. Before we left Microsoft, we had been talking about all of these things. We wanted to pursue something different. We wanted to stop working. We wanted to start from scratch in entrepreneurship. I think being in the Valley, there are a lot of discussions and thoughts on why engineers would have dreams about it. I don’t think anyone initially took us seriously, including our families. I felt that startup entrepreneurship is a subject that people like to talk about. I don’t think they realized that the two of us were really serious about it. So, when the day came when I was talking to my husband to say, “Are we really going to do it?” My colleagues and my husband all felt that we were nuts. We had great jobs, and we had established our reputation, and we were highly successful, and we wanted to give all this up to start something that was completely unknown? The two of us, obviously, if you see our background, probably could have the good judgment to say at that time, “We probably don’t know too much about it.” That was the first reaction. Then I was talking to my husband, and I told him, “What do you think about that? To think of me as a housewife, except I just don’t do that. I’m not working anymore, you need a housewife, except I don’t do housewife things.” He looked at me, and he said, “You were never a housewife. Now you want to stop earning money completely?” The two of us, Fang and I, went to our lab director, and we told him that we were leaving. We wanted to quit. We talked about this and that the two of us wanted to leave. We said, “What are we going to say? We’re going to tell him this is our opportunity. We want to start this company unknown. We don’t have a name yet, but that’s what we want to do.” He was shocked. He looked at us and said, “Do you really know what you’re working into? Are you ready? Do you know what a startup is like?” He was like, “Well, the two of you are doing great. We’d love for you to come back. You’re going to lose a lot on the table up front. You have stocks, etc., and you’re going to give all this up and just leave? What if in a few days, you realized, or maybe two months down the road, this is not what you want, and you’re going to lose a lot, so think carefully.” What he encouraged us to do was to talk to a few folks who had startup experience, and then understand it and ask, “Are we ready for this?” I think that was good advice, so Fang and I did our work. We talked to people, and we also talked to some of our friends. In the end, a few weeks later, we talked to him, and he said, “How is it?” We told him, according to everybody’s comments and suggestions, we were totally not ready. But at the same time, we still wanted to do it. Everything is a start. “We’re not ready. We want to get ready. We cannot get ready at Microsoft. We need to leave Microsoft and get ready.” So we determined that. That’s how it started.

Alejandro: Very interesting. I understand, as well, that when you guys finally gave your notice and started thinking about what you guys were going to be executing on, what you would be creating and building, I know that perhaps the reaction from your friends and family was different from those customers that you were going after. Tell us about this.

Yinglian Xie: I think from our past experiences, we had also been working on security, AI, machine learning. So, it was not a completely unrelated area except that we wanted to work differently. Before, we were doing more project by project, some specific problems. Now, coming out, we wanted to build something common to solve a lot of people’s problems together. We didn’t want to solve problems one by one. So, that never scaled. That’s what we wanted to do. We had friends and the people we worked with in the past while we were in Microsoft who had talked to us and consulted us for our opinions. Those are the ones we immediately thought might be early customers that we should talk with to see if they wanted to work with us. So, we came out of Microsoft, and around that time, we said we wanted to have a company; we wanted to start something new. “Are you going to work with us?” They all said, “The two of you are great. We’d love to work with you” because they had approached us in the past to see if they could collaborate with us. Obviously, they said a lot of great things and they wanted to work with us. That gave us confidence that we might be able to work with these people as our early customers. It’s interesting that the reality is that when the two of us decided we were going to quit and we left Microsoft, and we went back to these friends, early customers, and said, “Now, here we are. We’re available, the two of us. Are you going to work with us?” Everybody felt, “Well, I probably don’t want to be the first guinea pig. So, no.” That was, I would say, a lot of early rejections. That’s probably not surprising.

Alejandro: What did you learn about rejection?

Yinglian Xie: When we left Microsoft, it was wintertime. That first winter, when I look back, it started in December, January, it was also like this year, rained a lot and very cold. We went to a lot of different customers, and we went to cities a lot. Back then, at Microsoft, we would hardly go to cities. Each time we went to a city as a whole, we would take planes or trains. We drove a lot that winter to cities. We still got a lot of rejection. It felt miserable at that time in retrospect. But at the same time, we had the two of us. That felt like sort of the lucky thing. One of the lucky things really is to have Fang as my co-founder, and we worked together for a long time. We helped each other. We talked to each other. We said, “Let’s build something.” It was that kind of belief. We continued to push up.

Alejandro: Got it. What ended up being the business model?

Yinglian Xie: Our business model, DataVisor, we are a SaaS provider of a variety of services and platform tools to solve fraud problems for large consumer-facing enterprises. For example, we see a lot of fraud problems for the financial industry. People have all kinds of fraud, like application fraud, transaction fraud, and money laundering. For the customers in the social commerce industry marketplace: promotion abuse. You also have that transaction, so the fraud as well. Then you have these fake reviews, content abuse, and therefore marketplace you have buyer/seller fraud. So, a variety of different frauds are going on. Our mission, DataVisor’s mission, is to restore trust for these connected online enterprises as well as traditional industries. We provide a variety of AI and technology tools and platforms to empower them to do that.

Alejandro: Very cool. Talk to us about fundraising. I assume that for something like this, you need money to really execute. So, how did you go about raising that capital?

Yinglian Xie: If we look at our fundraising experience, I would say that’s probably some of the things that are going on relatively smoothly and maybe better than we anticipated. I would say when we got to Microsoft, we had no expectations to know how difficult or easy fundraising is. That’s one of the things we’ve got to do. We don’t know what the subject is going to look like. In the beginning, we worked at getting some angel support from friends, past colleagues, and mentors. Luckily, we did have some mentors and friends who were committed to support us. That assured us as the first step to say, “Come out. We will get some baby-step support.” I think the lucky thing is that we also are in the Silicon Valley location, where there are a lot of great VCs. Quickly after we left Microsoft, we were approached by some of the VCs who heard that we were leaving Microsoft and wanted to talk to us. Actually, we were very surprised that the VCs in Silicon Valley were looking for great people to work with as well in different aspects, so we were quickly approached by people.

Alejandro: How did they know that you were leaving?

Yinglian Xie: That was actually surprising to us as well. Apparently, in the Valley seems the whole entrepreneurial startup work is very connected, and you always will find the companies looking for great people. With this network connection, sometimes people are looking for co-founders. We were approached by a VC whose life in that situation was looking for co-founders for one of the entrepreneurs they were supporting, and they heard that the two of us were available. They reached out to us to say, “You want to do something. You want to start a company. Why don’t you join this company that their founding as co-founders with a similar related topic in the big security industry area?” So, that’s kind of the spot when we got the chance to be connected, learn a little bit. The two of us had been working there; we had our own mind and thoughts, so that led to us saying, “No, thank you very much. We’d love to work with you. These are great people, but we have our own ideas. We want to work on our own company. We have to reject this offer.” Then, you would have these VCs say, “Well, we really like you as great people. Let’s look at your ideas.” That’s the start. Once we started that, we were looking at maybe, we should talk to a few more. We don’t want to just talk to one VC. Maybe talk to a few more. We were not in a position to talk to many. We only needed a small amount of support at the beginning, so that was the beginning of the fundraising.

Alejandro: Got it. How much capital have you guys raised to date?

Yinglian Xie: To date, we have raised a fair amount. I would say of the typical Series Seed, plus company and probably close to 100 million in that ballpark between 1,500 million. Back then, looking at the first fundraising, 30 days, we were thinking about first only about angel money, the 100k. That’s what we were looking for the initial seed. When we got to VCs, we increased that expectation maybe, too, because of the fact we were working with them. They were talking to us about maybe thinking about 750k. But in the end, I would say the VCs wanted us to take more, so that very first fundraising actually led to 3-million dollars first.

Alejandro: I understand as well Yinglian, that you guys also raised money from not only the U.S. but also from China. What’s the difference in mindset during discussions and during pitching to a U.S. investor versus a Chinese investor?

Yinglian Xie: Yes, that’s an interesting topic. I want to say that it wasn’t intentional that we wanted to go out to pitch to China investors. It’s pretty much the nature of work. We are a very global company in terms or our customers as we worked with these larger consumer-facing companies. These definitely improved, for example, large internet-type of companies and social commerce and [0:30:31] companies. Many of these large enterprises are in China. The fact that the large Chinese companies are willing to become our customers even when we started to remotely, like in the U.S., I think attracted some of the investors when they came to the Valley to talk with us of accepting their money so that they could help us seriously expand into China. I think that was the start of when we started considering taking money from investors in China as well. It was not about investors in China. It was really about going global because our customers are global. If you look at DataVisor today, we have customers not just in the U.S. and China, but we have many customers in Europe, Southeast Asia, these different places. That’s where we feel super proud of solving problems across the globe because if you look at security fraud issues, that is a global issue. These attackers are everywhere, and [0:31:36], and attacks that you receive from the U.S. are not just originating from the U.S. They can originate from anywhere in the world, and that’s the same thing. That’s a start, but I would say the two different investors are slightly different. In particular, I would say the investors from China want to focus more on the growth perspective compared to more investors in the U.S. that are more traditional, the enterprise. China is more focused more on consumer-facing. They’re very experienced with consumer-facing. I think they brought to the table a lot of the knowledge and the value for working with companies like those. I think it’s very helpful as well.

Alejandro: Very cool. How many people do you have now in DataVisor? I read it is north of 100 people. Is that right?

Yinglian Xie: We have around 150 people now, globally.

Alejandro: Very nice. Let’s say, Yinglian, you go to sleep tonight, and you end up sleeping for five years in a row. Then, all of a sudden, in five years, you’re waking up in a world where the vision of DataVisor is fully realized. What does that world look like?

Yinglian Xie: That definitely would be a nice topic to talk about. I envision DataVisor to be a company that plays a leading role where we lever the best technology to solve a variety of fraud problems. I would say coming from academia work, coming from where I was, always challenging the state of art and always that the mission is to advance the state of art. I would say DataVisor carries the same mission. Our goal is not to provide ‘a’ solution, but our goal is to provide some of the best solutions in the world. Then really benchmark ourselves, our team, as being the team that we wanted to do something the best in the world. Therefore, we are committed to improving our technology and product to challenge the team to reach that goal. I want our technology to be the leading one that solves some of the hardest problems, and at the same time provide a variety of the choices to the customers of different stages of leading to the problem we understand like the customer at different growth stages, they probably would need a different variety of solutions. Some of them require more fraud-detection services. Others are more a platform-flavor that the value of the complementary solution and [0:34:44]. So, how do we enrich our product portfolio and not only have the best technology, but also have the rich needs, and also have some of the best user experience as well delivering for these customers in a global sense? That’s where we want to be. At the same time, we not only want to solve these difficult security problems, but we also believe many of the technologies and problems we develop can be expanded to solve broader issues related to this AI and machine learning. For example, in risk control areas and analytics area. I see that our technology can gradually expand across multiple industries. And, obviously, my near-term like a dream, like you said, to wake up is, for one thing, we can have the best technology product to solve problems for everyone and become the leading one in the fraud and risk area. I’ll be very happy. That’s our first dream. Longer-term, I want what we provided, what we enabled our customers can be used to broaden that vision to help with many different issues as well and to bring value. I would say that is my ultimate vision and goal.

Alejandro: Very nice. There’s definitely a lot happening in your space, and definitely, it’s a very hot space. There’s one thing, and that is as an entrepreneur is to be able to be in a space or build a business that you’re doing it at the right time in history. That’s where you guys are, which is very cool, Yinglian. I want to ask you one question that I typically ask the guests that come on the show. That is, if you had the opportunity to go back in time and have a chat with your younger self, Yinglian, let’s say those days when you were still at Microsoft maybe chatting with Fang about whether or not it would make sense to give your notice and make it happen. Knowing what you know now, if you could have that conversation and give yourself one piece of business advice before launching a business, what would that be and why?

Yinglian Xie: That’s a very good question. I want to say this one piece of advice that I would give to everyone and is probably very specific to me because I came from academia immediately to the other section of an entrepreneur. But at the same time, I would say to be very openminded and to listen to what the customer wants. At the same time, we have a lot of great ideas. I feel what would help us along the way is to work with the customers and to feel what they want and to bring value to these customers. I would say, do not do anything that would deviate from that: having a great product, solving their problems, and to guide us. Whatever great ideas, we need to generate value. This is what we feel would be super helpful. We’ve been doing that. I feel we could have done even more in the early days to make us faster.

Alejandro: Very nice. Yinglian, for the folks that are listening, what is the best way for them to reach out and say hi?

Yinglian Xie: We can always be reached by coming to our website. We can show demos, and we have ChatBlock. That’s another way we’re leveraging the best technology to be connected to the world. Feel free to come to our website, DataVisor.com, to book, for example, a demo request and trial request. For anybody who wants to chat with me specifically, I’m always available to be reached by LinkedIn and by email, as well.

Alejandro: Wonderful. Yinglian, thank you so much for being on the DealMakers show today.

Yinglian Xie: Thank you so much for having me. It’s a great pleasure to have this conversation.

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